Systems and methods for converting and delivering medical images to mobile devices and remote communications systems

ABSTRACT

A system for automated conversion and delivery of medical images. In an example implementation, a server is configured to retrieve a medical image file including medical data and metadata, in a medical data format, determine an output destination type based on the metadata, identify standardized format specifications based on the determined output destination type from the retrieved metadata, convert the medical data into a format compatible with the identified standardized format, and transmit an output message of the converted medical data to at least a recipient delivery address.

RELATED APPLICATIONS INFORMATION

This application is a continuation of U.S. patent application Ser. No. 15/976,069, filed on May 10, 2018 and is a continuation of U.S. patent application Ser. No. 12/904,870, filed on Oct. 14, 2010, now U.S. Pat. No. 9,984,203, and also is a continuation of U.S. patent application Ser. No. 13/045,448, filed on Mar. 10, 2011, now U.S. Pat. No. 8,108,432, both of which claim priority under 35 U.S.C. 119(e) to U.S. Provisional Patent Application Ser. No. 61/251,334, filed Oct. 14, 2009, and entitled “CONVERTING AND DELIVERING MEDICAL IMAGES TO MOBILE DEVICES AND REMOTE COMMUNICATION SYSTEMS,” all of which are incorporated herein by reference in its entirety as if set forth in full.

BACKGROUND 1. Technical Field

The embodiments described herein are related to delivery of medical image records, and more particularly to the automatic conversion of medical image file for delivery to mobile devices and/or remote communication systems.

2. Related Art

Medical diagnostic devices and medical imaging systems have become increasingly complex in recent years. In response to the increasing challenges in digital imaging technology, the American College of Radiology (ACR) and the National Electrical Manufacturers Association (NEMA) developed the Digital Imaging and Communications in Medicine (DICOM) standard. DICOM is a standard for handling, storing, printing, and transmitting information in medical imaging. It includes a file format definition and a network communication protocol. The network communication protocol is an application protocol that uses TCP/IP to communicate between systems. One of the goals of the standard is to make uniform the transferring of medical images and information between viewing and scanning sources to allow users of different imaging software and/or hardware to share information. DICOM files can be exchanged between two entities that are capable of receiving image and patient data in DICOM format. DICOM enables the integration of scanners, servers, workstations, printers, and network hardware from multiple manufacturers into a Picture Archiving and Communication System (PACS) for storing and downloading of digital images. The different devices come with DICOM conformance statements that clearly state the DICOM classes they support. DICOM has been widely adopted by hospitals, and is gaining popularity in smaller dentists' and doctors' offices.

DICOM files commonly contain images; therefore, they are often referred to as DICOM images. But it will be understood that a DICOM file does not necessarily need to include an image. Rather, such a file can include measurements or report data. Thus, DICOM files may contain media data, such as, video and audio data, or no media data at all. In that case, DICOM files may contain only metadata identifying the originating modality, the operator, or the patient being examined. Modality here refers to any image generating equipment in medical imaging, such as, Ultrasound (US), Magnetic Resonance Imaging (MRI), Computed Tomography (CT), Positron Emission Tomography (PET), radiographs, and the like.

The type of data and amount of data available in any one DICOM image file varies. A DICOM file is generally structured using data identifying Patient, Study, Series and Instance in that hierarchical order. A Patient can be involved in a number of Studies (cases), which in turn may contain a number of Series (examination or visits), which in turn may contain a number of Instances (files usually containing images). It means that a DICOM file can be unambiguously identified and fitted into that hierarchy. All DICOM files contain an identifier for the generating modality. In other words, the identifier will reflect the equipment or location in which the file was originated. The files also contain timestamps pertaining to both the file itself (Instance) and the Series. Using the timestamps and the originating identifier, an image can be unambiguously identified using that data without involving any identifiable patient information to safeguard patient privacy issues. In addition, DICOM file format differs from other data formats in that it groups information into data sets. For example, a file of a chest X-Ray image actually contains the patient ID within the file, so that the image can never be separated from this information by mistake.

Most PACSs handle images from various medical imaging instruments, including US, MRI, PET, CT, and the like. Electronic images and reports are transmitted digitally via PACS; this eliminates the need to manually file, retrieve or transport film jackets. A PACS consists of four major components: the imaging modalities, such as, CT and MM; a secured network for the transmission of patient information; workstations for interpreting and reviewing images; and long and short term archives for the storage and retrieval of images and reports. Combined with available and emerging Web technology, PACS has the ability to deliver timely and efficient access to images, interpretations and related data. PACS breaks down the physical and time barriers associated with traditional film-based image retrieval, distribution and display.

Medical imaging devices typically output digital image data. The overwhelming majority, if not all, of such devices use the DICOM standard for both image file format and network transfers. These images are generally not readable by consumer image viewers or mobile devices. Therefore, patients who wish to share their medical images struggle with conversion and delivery of these images. A good example is to share images from an Ultrasound examination during a pregnancy. The future parents usually would like to keep, share and display the images of their future child. They might also conceivably want to send these images to their friends' and relatives' cellular phones or email accounts. They might even want to post them on a social network, or they might just want to keep them in their personal digital “photo album”. All of these events would require them to either scan a printed hard-copy of the image, or to find, purchase, install and learn to use DICOM viewer software package with export capabilities. These software packages are usually not readily available or they are not economical for limited use.

It should also be noted that this issue is not necessarily limited to DICOM files. In general, there is no real method for a patient to view images related to their condition, treatment, status, etc. Moreover, there are few, if any effective means by which a doctor or clinician can quickly and remotely retrieve images for diagnostic or other purposes.

In fact, many smaller medical practices, such as, small clinics, doctors' offices, and dentists' offices also suffer from an inability to convert, deliver, and receive medical images economically and timely. These facilities usually do not have the technical support-staff or finances to run a full PACS for image archiving and delivery to remote expert doctors for second opinions and consultations. They often resort to using films, or writable CDs which are sent by mail or messenger. This is both slow, environmentally unfriendly and, in the case of using unregistered postal delivery, insecure. The cost of running a PACS is not just paying the licensing fees. Major investments in advanced infrastructure including the surrounding software, hardware, and facility, as well as the cost for educating staff, and the hours spent on administration will add to the cost of running a PACS. These major investments are expensive, therefore, usually out-of-reach for most small businesses.

SUMMARY

Systems and methods for the quick and easy distribution of medical images to a plurality of output modalities in a manner that maintains the highest possible image quality and resolution are described herein.

According to one aspect, a system for automated conversion and delivery of medical images, comprising: a communication interface; a data storage system configured to store a plurality of medical images, meta data associated with the plurality of medical images, converted medical images, a plurality of standardized format specifications for a plurality of destination devices and services, and a plurality of message templates; a server coupled with the data storage system and the communication interface, the server configured to: receive a medical image file via the communications interface, the medical image file comprising medical data and meta data, the medical data having a medical data format that complies with the digital imaging and communication in medicine standard, determine whether the medical data includes a medical image data, determine an output destination type, wherein the output destination type is an output device, service, or both, based on the meta data, correlate the output destination type with one or more of the plurality of standardized format specifications and with one or more of the plurality of message templates, convert the medical data format associated with the medical data based on the standardized format specifications that correlate with the output destination type, assemble at least one output message that includes the converted medical data based on the message templates that correlate with the output destination type, and transmit the output message to at least one destination via the communication interface.

According to another aspect, a method for automated conversion and delivery of medical images, comprising: storing a plurality of medical images, meta data associated with the plurality of medical images, converted medical images, a plurality of standardized format specifications for a plurality of destination devices and services, and a plurality of message templates; receiving a medical image file via a communications interface, the medical image file comprising medical data and meta data, the medical data having a medical data format; determining whether the medical data includes a medical image data; determining an output destination type, wherein the output destination type is an output device, service, or both, based on the meta data; correlating the output destination type with one or more of the plurality of standardized format specifications and with one or more of the plurality of message templates; converting the medical data format associated with the medical data based on the standardized format specifications that correlate with the output destination type; assembling at least one output message that includes the converted medical data based on the message templates that correlate with the output destination type; and transmitting the output message to at least one destination via the communication interface.

These and other features, aspects, and embodiments are described below in the section entitled “Detailed Description.”

BRIEF DESCRIPTION OF THE DRAWINGS

Features, aspects, and embodiments are described in conjunction with the attached drawings, in which:

FIG. 1 is a diagram illustrating an example system for the automatic conversion and distribution of medical images to any of a plurality of output modalities in accordance with one embodiment;

FIG. 2 is a high level block diagram illustrating certain components of an example data conversion and delivery system that can be included in the system of FIG. 1 in accordance with one embodiment;

FIG. 3 is a flow chart illustrating an example automated message creation process performed by the data conversion and delivery system of FIG. 2 in accordance with one embodiment;

FIG. 4 is a flow chart illustrating example type of information and data that can be examined in the process of FIG. 3 in accordance with one embodiment;

FIG. 5 is a flow chart illustrating an example process for the use of information embedded inside of the metadata included with incoming files by the data conversion and delivery system of FIG. 2 in accordance with one embodiment;

FIG. 6 is a flow chart that illustrates the operation of an image converter module that can be included in the data conversion and delivery system of FIG. 2;

FIG. 7 is a flow chart illustrating a typical use of a Web GUI that can be included in the data conversion and delivery system of FIG. 2 and its streamlined interface for finding an image by the originating modality without any identifiable patient information in accordance with one embodiment;

FIG. 8 is a flow chart illustrating a variation of the typical use of the Web GUI and its streamlined interface for finding an image by using a piece of identifiable patient data in accordance with one embodiment; and

FIG. 9 is a diagram illustrating an example system for the automatic conversion and distribution of medical images to any of a plurality of output modalities in accordance with another embodiment.

DETAILED DESCRIPTION

FIG. 1 is a diagram illustrating an example system 100 for the automatic conversion and distribution of medical images to any of a plurality of output modalities. The term output modality is used to refer to various types of devices, systems, and services, several examples of which are provided below. As can be seen, system 100 can comprise a plurality of source medical imaging modalities 10, such as Ultrasound, MRI, CT and PET equipment, a local PACS 20 (typically source image archive-servers), or any other device capable of sending medical data such as DICOM data, commonly medical images. Modalities 10 and PACS 20 can be connected, e.g., with a Central Computer System (CCS) 30 via the Internet 60 through a router 50 usually provided with encryption and firewall protection.

Central Computer System (CCS) 30 can include a data conversion and delivery system (DCDS) 32 for processing the medical data. The CCS can comprise one or more servers, and include one or more a processors or CPUs, memory associated with the processor(s), a data storage module, a display means, and an input/output interface means. It should be appreciated that various other peripheral devices and modules can be connected to the CCS, such as other servers, other data storage modules, or intrusion detection systems. The CCS can also be a cluster of interoperating servers, each taking care of a specific task within the system. Similarly, all the modules shown in FIG. 2, and described below can each be a separate server in such a cluster, so as to distribute the load and increase the capacity of the system.

DCDS 32 can be configured to convert medical images associated with the medical data into, e.g., consumer-friendly images, video, or both. DCDS 32 can then in turn send these converted images to a number of destinations, or output modalities 40 as directed by the user/operator of DCDS 32 or as dictated by information included in the medical data. These destinations 40 can be, for example, a web site such as a social networking site including, e.g., Twitter, Facebook, and Google Health; cellular phones; PDAs; Email accounts; or any computer system capable of accepting data via protocols such as, e.g., SOAP and REST. DCDS 32 functions in such a way that it allows source modalities (10, 20) to be protected by the most rigorous of firewall settings 50, while still allowing transfers to take place over the internet 60. The original source image data may optionally be sent to the destinations 40 without any processing or conversion.

For example, when a patient undergoes an ultrasound examination during pregnancy, the ultrasound images can be sent to DCDS 32 for conversion into a set of images that can be sent the parent's social networking web page, their mobile device, their friends and families devices or web pages, etc. More specifically, a nice sequence of the fetus waving its arm can be captured and stored during the ultrasound examination by the operator. The ultrasound operator, usually a nurse or technician, sends the stored, e.g., DICOM file to DCDS 32. The nurse, technician or any trusted employee at the patient's facility (user) can use a remote graphical user interface (GUI) interfaced with DCDS 32 to bring up the desired sequence sent by the source modality 10. The user can then enter the cellular phone numbers, web account information, email addresses, etc., as well as any personal message that the patient indicates, and then start the delivery process. The, e.g., DICOM file, now converted into a cellular phone compatible video format, e.g., 3gpp, can then be sent as a multimedia message to the mobile phones, and files converted to other appropriate formats can also be sent to the given email and web accounts.

Alternatively, the nurse or technician at the patient's facility can enter the patient's cellular phone number in the patient information field on the ultrasound machine. On receiving the, e.g., DICOM data file, DCDS 32 can be configured to then locate that number embedded in the DICOM data file, and automatically forward the converted image or video file after processing to the desired locations as specified by the patient. Examples of these processes are described in detail below.

FIG. 2 is a high level block diagram illustrating certain components of an example DCDS 32 in accordance with one embodiment. It will be understood that the diagram of FIG. 2 is for purposes of explanation and illustration and is not intended to restrict the embodiments described herein to any particular architecture or design. Nor is FIG. 2 intended to provide a detail view of all components of an example DCDS 32. In operation, a request from a modality 10 can be handled by an input stage, consisting of a Receiver 203 and Storage & Parser 204. The Receiver 203 can be configured to authenticate the connection from the source modality 10, and to handle the network transactions necessary to complete the request.

Storage & Parser 204 can be configured to parse the received data and to store any image data 205 and all metadata 206 in storage system 214. For example, the image data 205 can be stored as binary data, while the metadata can be stored as structured data allowing typical structured access to the data, such as, searches and associations between different items. Storage & Parser 204 can be configured in certain implementations or under certain conditions to strip all sensitive patient information from the incoming data file. For example, an operator of the system can use a Graphical User Interface (GUI), such as a Web GUI 208 to selectively set the parts of metadata that are considered to be sensitive. Alternatively, the system can be programmed to automatically determine which fields in the meta data are sensitive. This process is called anonymization, and it is performed in order to protect the patient's privacy. Anonymization is discussed in more detail below.

In certain embodiments, an event signal can be triggered indicating that the newly stored data has been added. When Event System module 209 receives an event signal from the parser 204, it can be configured to determine what action, if any, should be taken as a result. For example, if rules for automatic delivery have been set, and the appropriate metadata values are found in the newly received data stored in structured database 206, then Event System module 209 can be configured to signal the Output Module 213 to send the converted data as instructed by the automatic delivery rules. This process is also described in more detail below.

Output Module 213 can be configured to accept calls from other parts of DCDS 32 containing general data, information to send, and number of delivery destinations, including email addresses. For example, the data can include a text message, a reference to a, e.g., DICOM image, two cellular phone numbers, and one email address. The Output Module 213 can be configured to assemble the appropriate formatted output “packages”, or messages, and send the resulting messages using a modular plug-in-based architecture. A plug-in (not shown) for each corresponding type of destination can be included and used by Output Module 213.

In the example provided above, when a service call is received by DCDS 32, Output Module 213 can assemble one MMS message packet containing a jpeg version of an image and message text, all combined and encoded according to the MMS specifications. This message can then be sent twice, first to each phone number destinations requested, and secondly, to each email address destinations specified.

Output Module 213 can request a converted image from Image Converter 211, identifying the original image and specifying the requested format and dimensions. Image Converter 211 can be configured to then look for an existing image in the Converted Image Cache 212 that matches the request. If no match is found, it can generate an image from the original image data 205. The Image Converter 211 can be configured to use the metadata 206 of the original image stored in database to determine if the requested format is appropriate. If not, it can respond with an error. For example, requesting an mp3 audio version of a still image would result in an error, while requesting a jpeg still image of a multi-frame DICOM image file (effectively video) would be proper.

Image Converter 211 can be configured to respond to an event from Parser 204 and perform common conversions preemptively. This will improve the responsiveness of the system components, in particular, the Output Module 213 and the Web GUI 208; however, the trade-off is an increase in storage required, and also a slight decrease in the overall security level.

A Web GUI 208 provides, e.g., medical staff with remote access to DCDS 32 via a secured web browser connection (https) 202. Such a Web GUI 208 can provide an interface to perform administrative tasks such as setting up rules for Event System module 209, as well as an optimized interface for identifying images and sending output messages. The typical operations of these interfaces are described in detail below.

Web GUI 208 can operate on the structured metadata 206 to find and identify images. It can be configured to request conversions from Image Converter 211 to, e.g., display thumbnails and previews of images, and to provide service request forms where output messages can be specified and send on to Output Module 213 for delivery.

An adaptable Garbage Collector 207 can continually evaluate the state of all data and compare that to configurations made by an administrator of the system. The configuration can set certain criteria that items need to meet in order to remain in the system or be deleted from the system. One basic criterion can be the age of an item. For example, if an item has been stored over a week ago or certain number of days ago could be automatically deleted. Other automatic deletion criteria can be the number of times an item has been previously sent, system state information stored, and the value of any metadata. This feature is in part useful for keeping the resource usage down, and also to aid patient confidentiality by removing patent data that the system is no longer needed to maintain.

It should be noted that in some embodiments the images are to be used for clinical or diagnostic purposes. In such instances, it is often required that the image that is ultimately displayed on the device used for viewing the images maintain a certain resolution or image quality. As such, in certain embodiments, one or more of Parser 204, Event System module 209, and Image Converter 211 can be configured, either alone or in combination, to recognize that the image is being viewed in a diagnostic or clinical application. Such recognition can be based on information included in the meta data, information stored in Image System 214, or information provided via GUI 208.

For example, the address or device identified in the meta data for receiving the image can be recognizable as an address or device associated with a clinical or diagnostic application, the image or series identifier can also be associated with a clinical or diagnostic application, etc. Alternatively, an operator can indicate through GUI 208 that images to be sent are intended for clinical or diagnostic purposes.

When it is determined that the images are to be used for clinical or diagnostic purposes, then Image Converter 211 can be configured to determine, e.g., based on information stored in storage system 214, the required resolution or image quality. For example, resolution, image quality, or both for various types of images, clinical applications, etc., can be stored in storage system 214. Image converter can then determine the correct image resolution and quality and covert the image in accordance therewith. In certain embodiments, DCDS 32 can be configured to determine whether the identified output device or address is capable of displaying the converted image with the requisite image resolution and quality before sending the image. If the device or address is not capable, then DCDS can generate an error message or other notification indicating such. The error message can be displayed through GUI 208, on the device, or both.

As noted above, DCDS 32 can be configured to take an incoming medical image file and automatically convert it for distribution to and viewing by any of a plurality of output modalities. FIG. 3 is a flow chart illustrating one example embodiment for an automated message creation operation performed by DCDS 32 in accordance with one embodiment. In the example of FIG. 3, it is assumed that destination information, e.g., output modality information is included in a medical image file received by DCDS 32. In other embodiments, a user can access DCDS 32, e.g., through GUI 208 and specify which files should be sent to which output modalities; however, a powerful aspect of DCDS 32, as configured in accordance with the systems and methods described herein, is its ability to automatically determine the destinations and to convert and format the data appropriately as described below.

In step 320, a file is received and the headers associated therewith are examined to determine various information. The medical image file received by input 203 will often include metadata that provides information related to the medical data or images included therewith. For example, in a DICOM file, the medical image file will include a header that comprises a plurality of fields. These fields are generally the same for each input modality 10. Thus, DCDS 32 can be configured to examine the header fields to determine various information as described in detail below and with respect to FIG. 4.

In step 322, an output destination type, or modality can be determined. For example, the header can include information identifying recipients of the images included in the image file. Or more specifically, the header can include information identifying output modalities associated with various recipients or services, e.g., such as an online photo album page, site, or service; a social networking page or service, a mobile device, etc. Basic types of destinations can include a mobile device, such as a cellphone; an email account; a Web-Application Specific Interface (API), e.g., associated with an online site or service, etc. Thus, DCDS 32 can be configured to examine the header file and determine associated output devices or services, i.e., modalities.

Whenever possible, DCDS 32 can be configured to then retrieve specific characteristics of each destination type as indicated in step 324. These characteristics can include capabilities and physical characteristics of the destination device and specifications and limitations of the network class and message type. This information is then used to determine the output formatting and other specifications needed for each output modality. For example, this information can be used for adaptations of the image data based on specifications for the type of message being sent, e.g., e-mail has limitations in specification and common practice that can be adapted for; and MMS has very different limitations that can be adapt for.

The capabilities and characteristics determined in step 324 can include frame size, i.e., pixel dimensions of an image or video, e.g., 640 by 480 and the like; data rate or data size, e.g., MMS messages can commonly not exceed 300 KB total size, e-mail attachments exceeding 10 MB are often not accepted, etc.; supported encoding format, e.g. mpeg 4, jpeg, etc.; and message layout rules, i.e., how a message can be composed for the destination, e.g. MMS is made of “pages”, each able to display a single image or video and a single text along with playing audio while e-mail is capable of HTML layouts and can hold attachments of any file type, etc.

In step 326, a basic compatibility check can be performed to determine whether the data included in the image file can be delivered in a format compatible with the output modality. For example, if the image data includes video data, then a determination can be made as to whether the output modality is capable of receiving and displaying video data.

The most suitable delivery format is then chosen in step 328 to ensure the output message that is ultimately generated includes the best quality data that the output modality can handle. This can be important for example in clinical settings or settings where the data is being used for examination or diagnostic purposes. Resolution information suitable for diagnostic purposes and the ability of DCDS 32 to provide such resolution is discussed in detail below.

Then, in step 330 the data can be extracted and converted as required. For example, MMS messages allow only a very limited total message size. Therefore images or video in particular often need to be adapted and optimized to let the final message meet the format and specification requirements of a particular output modality. In contrast, e-mail messages often have no strict limit on size and therefore can accept larger files, e.g., higher resolution images or video. But even e-mail accounts can include rules limiting extremely large files and therefore even e-mail messages can require optimization of, e.g., video files to ensure sufficient quality but also to comply with size limitations.

If the incoming file is already encoded in a format compatible with the output modality, then often no conversion will occur in step 330 in order to preserve the highest possible image quality.

In step 332, the data can be anonymized as required by any applicable anonymization rules. For example, the data can be extracted and copied into a generic format so that certain data can be removed, redacted, etc. The data can then be converted to the final output format. Steps 330 and 332 can be performed in parallel or reverse order as required by a particular implementation.

In step 334, the converted data can then be assembled into an output message in accordance with the applicable formats and specifications determined in the preceding steps. Optionally, other data can be included with the message. This information can be manually entered, e.g., via GUI 208 or it can be extracted from the metadata accompanying the received file. Still further, the data can be data retrieved from configuration settings based on the set of characteristics described above.

In certain embodiments, the data components that are to comprise an output message are assembled according to template rules for the type of message being created. For example, the various template rules can be stored in Storage System 214 and accessed by Output Module 213 in order to assemble the output message. For example, MMS messages are based on a page metaphor where each page can contain an image or video, a text element, and an audio element. Thus, sending two or more images, or including text, audio, or both with the image(s) will then require the message to be assembled into several pages. By contrast, e-mail messages can include any number of images, attachments, etc., depending on, e.g., the message size restrictions.

Output Module 213 can then be configured to elect the appropriate output gateway for transmission of the assembled output message in step 336. For example, Output Module 213 can be configured to send an e-mail message to a SMTP server (not shown) and to send an MMS message to a MMS gateway (not shown).

FIG. 4 is a flow chart illustrating example type of information and data that can be examined in step 320. As can be seen in FIG. 4, when the file comes in, the metadata or more specifically the header can be examined to identify the input modality in step 420. In step 422, the compatibility of the modality determined in step 420 with the system can be determined. If compatible, then in step 424, specific characteristics of the data included in the image file can be determined. For example, whether or not the file actually includes any image or video data or whether the data is simply report or measurement can be determined in step 424. When an incoming file does include, e.g., report or measurement data, then such information can be extracted and stored in, e.g., a generic structured format in step 426. In step 428, any image data can then be extracted and stored as well and various characteristics can be determined such as binary encoding format, frame size, color bit depth, still image or video, etc.

FIG. 5 is a flow chart illustrating an example process for the use of information embedded inside of the metadata including with incoming files by DCDS 32 in accordance with one embodiment. The metadata, e.g., header fields can be used to ensure safe and secure delivery of the image data included therewith. For example, a DICOM image file can include a plurality of header fields that are key-value pairs in a number of datatypes, such as strings, numbers, dates, special measurement types, etc. Fields can be embedded in the and can be hard linked to the file for which the provide metadata. In this way, there is no way to mix-up header files and the associated data, since they are not separated.

In step 520, DCDS 32 can be configured to automatically track and record header fields for each network device sending images. In this way, DCDS 32 can identify the specific device associated with an incoming file. DCDS 32 can do this by recording which header fields are present for a particular modality 10 in step 522 and to then record the data included in device-dependent header fields for the associated modality in step 524. A particular device should always report the same values for, e.g., manufacturer, model name, model number, etc. Thus, DCDS 32 can use this information to identify a particular device.

In step 526, DCDS can detect any changes in the data and then take appropriate action. For example, changes to header field data that should not be changed, e.g., manufacturer information, can be an indication that the file has been tampered with or someone is trying to hack into the system. In response to detection of such changes, the system can log the event, notify an operator, place the incoming data in an approval queue, quarantine the data or any further data from the associated device, reject the data, rejecting the all future data from the device, to name just a few possible actions.

In step 528, DCDS can be configured to search the header fields for data that can identify an intended recipient as noted above. Identification can be in the form of an actual, e.g., e-mail address, mobile station International Subscriber Directory Number (ISDN), web site address, etc. In fact, such direct identification can be preferable as it takes advantage of the existence of the header fields. Identification can also be indirect such as an ID that can be used to look up a direct address, e.g., in a registry stored in storage system 214. It should also be noted that each field can include more than one piece of data and data of different types. Accordingly, any identifying or address fields can include telephone numbers as well as e-mail address, etc. Further, identifying data can be included in more than one field.

The DCDS 32 can be configured to then determine an action to take in step 528 based on any identifying data detected in step 530. Such actions can include sending an appropriate message to any addresses found, formatting messages appropriately as described above, notifying an operator, adding a message to a queue, e.g., for manual approval, locating and adding other data or information to an outgoing message, to name just a few.

Accordingly, FIG. 6 is a flow chart that illustrates the operation of DCDS 32 in more detail. Referring to FIG. 6, a Conversion Request 301 can be received containing, at a minimum, an internal identifier for the image, and a destination format. As noted above, the conversion request can be the result of information and data included in the metadata associated with an incoming file. As noted below, however, the request can also result from input received through GUI 208. Optionally, the request could contain new image dimensions to be scaled as output image to be sent. The Image Converter 211 can be configured to then determine the existence of the requested image 304 by trying to locate the metadata associated with it in metadata database 303. If no record exists for the requested image, the converter can optionally return a placeholder image (305, 308) or abort the conversion attempt 306. A placeholder is typically an image, video or similar media communicating that the requested image is unavailable. At this point, the converter also can also be configured to determine if the requested output format is feasible or not.

If a metadata record in database 303 does exist, then the converter can be configured to load the, e.g., DICOM image 307 from image storage 302 into a raw binary format. The Converter 211 can be configured to then determine if the image data should be resized to the dimensions provided in the request or to the dimensions required by the requested output format. For example a jpeg preview for the Web GUI 208 could be rendered in any dimensions that are suitable to the layout of the html document, while video for MMS messages have very specific dimensions to comply with the specification.

Next, the image data can be converted 311 to the requested destination format. The results can be saved to an image cache 312 and metadata records can be updated 313 to indicate the existence of the converted image. Finally, the converted images can be returned as a response to the request. Converter 211 can then return either the converted binary data directly or return a reference to its location in the image cache 313.

As noted, DCDS 32 can also be operated and interfaced with through the Web GUI 208. GUI 208 can enable both remote and local access the DCDS 32 and allows for images to be located within storage system 208. The images may need to be located or analysis or diagnosis or for sending to a specified destination or address.

Two primary ways for accessing files can be provided. The first way involves finding files without any identifying information. This is explained in detail with respect to FIG. 7; however, it should first be noted that each device sending files to DCDS 32 can be identified by recording and mapping header fields of incoming file transfers. The devices can also be at least partially identified based on their network address, AE titles used for the transfer, or both. Each device can then be given a name that is unique and preferable meaningful to operators. Files as well as their series, study, or both, can then be identified by the device they originated from, the time and date of the image capture, and header fields identifying the operator of the device used to capture the images.

Since no patient information is needed, DCDS 32 can handle anonymized data and no patient information can be gathered by the misuse of the system. Further, the most used images can be stored as the most recent images in the system. Thus, finding images can be made very efficient in this manner. Once the file, series, study, etc., had been found, GUI 208 can offer the operator direct access to features for viewing the images, sending the images, etc.

With this in mind, FIG. 7 is a flow chart illustrating a typical use of the Web GUI 208 and its streamlined interface for finding an image by the originating modality without any identifiable patient information (401-404) in accordance with one embodiment. When an image has been identified (405) the interface displays a service request form where the user enters output destination information and other message details. If the data validates (407) the required conversions are requested (408) from the Image Converter (211.) For all successful requests, the data is assembled by the appropriate output plug-ins (409-411) and the results are sent (412-414) to the appropriate destinations. Status information for each individual output is gathered (415) and returned (416 or 417) to the form view (405) for display. At this point, the user can choose to repeat the send process or return to finding another image.

The Web GUI 208 allows for sending groups of images that belong to the same, e.g., DICOM Series. The operating steps are similar to those illustrated by FIGS. 7 and 8. The Web GUI 208 also present interfaces for configuring the Event System 209, organizing and storing output destination addresses and other administrative tasks necessary. It is important to note that, as a security measure, the Web GUI 208 does not handle any authorization of source modalities allowed to store images or access privileges to those images. These important settings are only available through a separate method of access either locally or remotely. With the DCDS running on a Unix-style operating system, remote access would typically be via the Secure Shell (SSH) protocol. If the DCDS is running on a Windows operating system, remote access would typically be via Terminal Services. Both protocols are examples of secured remote access to the operating system.

The second way to access files is to use identifying information. For example, operators can search for files using patient information such as name, birth date, patient ID, etc. The operator can, for example, input a search term and if there is a match, the system can present all available studies. If multiple patients are returned, then they can be presented for selection. Once the patient is selected, and the associated file, series, study, etc., had been found, GUI 208 can offer the operator direct access to features for viewing the images, sending the images, etc.

FIG. 8 is a flow chart illustrating a variation of the typical use of the Web GUI 208 and its streamlined interface for finding an image by using a piece of identifiable patient data (501-504) such as, patient name, and birth-date, etc. Alternatively, any unrelated identifying password or PIN code can be utilized to avoid using real patient information to ensure patient privacy. After that, the processing steps as described above related to FIG. 7 can be followed.

In certain embodiments, CCS 30 can be interfaced with a server 902 that can be configured to host and support various value added services for, e.g., patients and family in relation to the images being captured by modalities 10 as illustrated in FIG. 9. For example, if the images are fetal ultrasound images, the server 902 can be configured to provide a variety of services for the parents, family, friends, etc. For example, the DCDS 32 can be configured to convert the images to a proper format or formats supported by server 902 and the related services. The images can be sent to server 902 and stored in storage system 904.

It will be understood that server 902 can actually comprise a plurality of servers, computers, routers, etc., as well as the appropriate software and firmware required to carry out the functions described herein. Further, storage system 904 can comprise one or more databases, one or more storage servers, as well as other physical storage mediums as required.

Server 902 can then be configured for example, to host a web site on which users can create accounts. The users can then access the images on the site and purchase images, pregnancy calendars, customized mugs, key chains, T-shirts, canvases, etc. Further, the site can be configure to present pictures, illustrations, information on fetus and child development, health and nutrition tips, etc. Such a site can enable such services as a registry, e.g., for a baby shower; automatic updates to friends and family; digital and viral gifts, such as baby images with digital lullabies; invites and thank you cards; etc.

A user can be charged a fee for setting up an account, e.g., a subscription fee, either one time or periodic, the user and family and friends can also be charged for the various products and services, or both.

In addition, kiosks 908 can be set up, e.g., in maternity wards that can provide at least some of the same services. Kiosk 908 can either be stand alone, i.e., interfaced directly with CCS 30, or can be interfaced with server 902 as illustrated. Thus, family and friends can order pictures and other goods, e.g., right in the waiting room.

Further, the user can continue to use the account even after the birth of the child. For example, the site can track the child throughout its child hood, or at least through the first few months or years. The site can be configured to send birthday reminders and announcements to friends and family or to inform of other special events, developmental milestones, etc. Moreover, the site can be configured to continue to present developmental information as well as health and nutrition tips for both mother and child.

In fact, it can be preferable to have the parent upload contact information for friends and family. In this manner, server 902 can be configured to continue to send birthday reminders to friends and family. In certain embodiments, the site hosted by server 902 can be affiliated with or host a “gift store” offering various products and services. Alternatively, or in addition, the site can offer discounts, coupons, etc., to various other business and stores. Since server 902 will have pertinent demographic information related to the child, e.g., residence information, sex, age, race, and possibly even parents age, profession, and other affiliations, the site can send reminders, gift recommendations, discount offers, etc., that are appropriate for the child and the family, popular with similar demographics, etc.

In this regard, it can be preferable to offer the user the opportunity to provide such demographic information. Thus, in one embodiment, the user can access the site and customize or provide profile information, contacts, preferences, etc. Algorithms running on server 902 can be configured to then use the information available to make product recommendations, etc. In fact, since server 902 will have information for individuals all over the world, the algorithms can be configured to use information for populations that share similar demographics, income levels, preferences, etc., to make recommendations.

In certain embodiments, a user can purchase items through the site, i.e., through server 902. For example, server 902 can be configured to accept credit card payment, a PayPal account, or for mobile billing. Thus, server 902 can be configured to process the transaction and either deduct an appropriate fee or charge a related business, affiliate, partner, etc., a transaction fee. Moreover, purchase information can also be fed into the algorithms and used to make future recommendations. In fact, the purchases of an entire related population can be used to make more targeted and appropriate recommendations.

Thus, as a child grows, the algorithms can be constantly updated and honed in order to make, e.g., gift recommendations. Recommendations that can be automatically sent out to friends and family over the years. As the database grows over time and with more and more users, the algorithms can be honed to provide ever more relevant and targeted recommendations.

It should also be noted that the database will necessarily include vast information about the relationships and connections between a large population. This includes direct links such as friends and family, but also more indirect links such as preferences, similar buying habits, etc. This type of interconnection information can be very valuable for targeted advertising and product recommendations as well as for simply tracking and mapping the interconnectedness of a large population.

It should be pointed out that such a site can be built around other conditions or events, such as a cancer support site, physical therapy support site, etc. It should also be pointed out that the merging of interconnectedness data for these various other conditions and events can extend the power of the information and lead to even better algorithms for targeting information and products and services.

It should also be noted that users can access the site via, e.g., the Internet using computers 914 and mobile devices 912. Further, the site can be interfaced with other social networking sites such as Twitter, Facebook, etc. In certain embodiments, the site can actually be converted to an application, or widget that can be exported to other sites. For example, a grandma can place the application on her Facebook page and receive updates and notices more easily without needing to log onto server 902. This can increase the interaction with the site, which can increase, for example, the amount of information and data available to server 902 as input to the algorithms described above.

While certain embodiments have been described above, it will be understood that the embodiments described are by way of example only. Accordingly, the systems and methods described herein should not be limited based on the described embodiments. Rather, the systems and methods described herein should only be limited in light of the claims that follow when taken in conjunction with the above description and accompanying drawings. 

What is claimed is:
 1. A system for automated conversion and delivery of medical images, comprising: a server comprising at least one processing device configured to: retrieve a medical image file, the medical image file comprising medical data and metadata, the medical data including at least medical image data in a standard medical format wherein the retrieved metadata indicates a recipient delivery address; determine an output destination type based directly on the retrieved metadata in view of the type of recipient delivery address; identify standardized format specifications based on the determined output destination type from the retrieved metadata; convert the medical data into a format compatible with the identified standardized format specifications of the determined output destination type; and transmit an output message comprising the converted medical data to at least the recipient delivery address.
 2. The system of claim 1, wherein the recipient delivery address comprises at least one of a cell phone number or an email address to determine the output destination type.
 3. The system of claim 1, wherein the output destination type is associated with device type determined based the recipient delivery address.
 4. The system of claim 1, wherein the output destination type is at least one of a mobile device, a medical application type, and a website.
 5. The system of claim 1, wherein at least some of the metadata is included in a header portion of the medical image file.
 6. The system of claim 1, further configured to store the converted medical data at least temporarily.
 7. The system of claim 1, wherein the server is further configured to identify a modality associated with the medical data based on the metadata.
 8. The system of claim 1, wherein the server is further configured to: anonymize the converted medical data; and assemble the converted and anonymized medical data into the at least one output message.
 9. The system of claim 1, wherein the server is further configured to identify specific characteristics of the medical data and extracting the medical data, wherein the identifying specific characteristics of the medical data comprises determining whether the medical data includes at least one of reports, measurements, and wherein the server is further configured to extract the medical data, convert the extracted medical data into a generic structured format.
 10. The system of claim 1, wherein the server is further configured to identify specific characteristics of the medical data and extracting the medical data, wherein the identifying specific characteristics of the medical data comprises identifying at least one of binary encoding format, frame size, color bit depth, and whether the medical data includes still images or video images, when determining that the medical data includes the medical image data.
 11. A computer-implemented method for automated conversion and delivery of medical images, comprising: retrieving a medical image file, the medical image file comprising medical data and metadata, the medical data including at least medical image data in a standard medical format, wherein the retrieved metadata indicates a recipient delivery address; determining an output destination type based directly on the retrieved metadata in view of the type of recipient delivery address; identify standardized format specifications based on the determined output destination type from the retrieved metadata; converting the medical data into a format compatible with the identified standardized format specifications of the determined output destination type; and transmitting an output message comprising the converted medical data to at least the recipient delivery address.
 12. The method of claim 11, wherein the recipient delivery address comprises at least one of a cell phone number or an email address to determine the output destination type.
 13. The method of claim 11, wherein the output destination type is associated with device type determined based the recipient delivery address.
 14. The method of claim 13, wherein the output destination type is at least one of a mobile device, a medical application type, and a website.
 15. The method of claim 11, wherein at least some of the metadata is included in a header portion of the medical image file.
 16. The method of claim 11, further comprising identifying a modality associated with the medical data based on the metadata, wherein the modality is based on whether the medical data includes reports, measurements, and wherein the method further comprises extracting the medical data, and converting the extracted medical data into a generic structured format.
 17. A non-transitory computer readable medium comprising instructions, that when executed by a processing device, cause the processing device to: retrieve a medical image file, the medical image file comprising medical data and metadata, the medical data including at least medical image data in a standard medical format wherein the retrieved metadata indicates a recipient delivery address; determine an output destination type based directly on the retrieved metadata in view of the type of recipient delivery address; identify standardized format specifications based on the determined output destination type from the retrieved metadata; convert the medical data into a format compatible with the identified standardized format specifications of the determined output destination type; and transmit an output message comprising the converted medical data to at least the recipient delivery address.
 18. The non-transitory computer readable medium of claim 17, wherein the recipient delivery address comprises at least one of a cell phone number or an email address to determine the output destination type, wherein the output destination type is associated with device type determined based the recipient delivery address, and wherein the output destination type is at least one of a mobile device, a medical application type, and a website.
 19. The non-transitory computer readable medium of claim 17, wherein the processor is further to: anonymize the converted medical data; and assemble the converted and anonymized medical data into the at least one output message. 